At a Glance
- Tasks: Design and implement predictive models to enhance marketing strategies.
- Company: Join a leading data-driven digital agency making waves in the marketing world.
- Benefits: Enjoy hybrid work options, competitive salary, and opportunities for professional growth.
- Other info: Work with top-tier clients and lead projects that shape data strategy.
- Why this job: Make a real impact on global brands using cutting-edge AI and analytics.
- Qualifications: Advanced skills in machine learning, Python, SQL, and strong communication abilities required.
The predicted salary is between 36000 - 60000 £ per year.
Location: Hybrid (London) or UK Remote
Are you a Data Scientist or ML Engineer ready to make an impact across the full data science lifecycle? Do you thrive in fast-paced environments, enjoy wearing multiple hats, and take pride in turning ideas into production-ready solutions? My client is a leading data-driven digital agency, looking for a Data Scientist/ML Engineer to join their high-impact Marketing Sciences team. You will be working on cutting-edge data science projects that directly drive campaign performance, customer engagement, and revenue growth for some of the world's biggest brands.
What You’ll Be Doing:
- Build & Optimise Models: Design and implement predictive models including causal AI campaign modelling, forecasting engines, pricing elasticity models, and recommender systems.
- Lead Projects & People: Guide a team of data scientists across multiple projects. Depending on experience, this may include upskilling those around you.
- Deliver Real Business Impact: Use predictive and prescriptive analytics to generate insights that translate into tangible improvements for client campaigns and marketing strategy.
- Prototype & Scale: Develop tools, frameworks, and self-service prototypes that showcase the agency’s capabilities.
- Client-Facing Influence: Present technical concepts clearly to both technical and non-technical stakeholders.
- Document & Collaborate: Work cross-functionally and ensure processes are documented and scalable.
Must-Have Experience:
- Extensive experience building machine learning models for marketing use cases.
- Advanced skills in segmentation, recommendation, campaign optimisation, forecasting, etc.
- Proficiency in Python, SQL, Bash, and Git. Familiarity with tools like Pandas, Jupyter notebooks, PyTorch.
- Experience with advanced techniques including CausalAI, NLP, RNNs, GraphAI, GenAI, and Computer Vision.
- Solid understanding of experimentation methods including A/B testing.
- Strong communication skills and ability to translate complex analyses into actionable insights.
Nice-to-Haves:
- Familiarity with marketing-specific measurement models such as Media Mix Modelling (MMM).
- Knowledge of model versioning (e.g. MLFlow), API frameworks (FastAPI), or building dashboards (e.g. Dash or Streamlit).
The Opportunity: You will work across multiple industries and household-name brands, contributing to meaningful campaigns powered by cutting-edge AI and analytics. This role offers variety, high visibility, and the opportunity to shape data strategy at both a technical and strategic level.
Data Scientist / ML Engineer in London employer: Xcede
Join a leading data-driven digital agency that champions innovation and collaboration in a hybrid work environment. With a strong focus on employee growth, you will have the opportunity to lead projects, mentor fellow data scientists, and make a tangible impact on high-profile campaigns for renowned brands. Our vibrant work culture fosters creativity and encourages continuous learning, making it an ideal place for those looking to advance their careers in data science and machine learning.
StudySmarter Expert Advice🤫
We think this is how you could land Data Scientist / ML Engineer in London
✨Tip Number 1
Familiarise yourself with the latest trends in machine learning and data science, especially those relevant to marketing. Being able to discuss recent advancements or case studies during your interview can demonstrate your passion and knowledge in the field.
✨Tip Number 2
Prepare to showcase your experience with specific tools mentioned in the job description, like Python, SQL, and PyTorch. Consider creating a portfolio of projects that highlight your skills in building predictive models and using advanced techniques such as CausalAI or NLP.
✨Tip Number 3
Practice explaining complex technical concepts in simple terms. Since the role involves client-facing responsibilities, being able to communicate effectively with both technical and non-technical stakeholders will set you apart from other candidates.
✨Tip Number 4
Network with professionals in the data science and marketing fields. Attend industry meetups or webinars to connect with others who may have insights into the company or role, and don’t hesitate to reach out on platforms like LinkedIn to express your interest.
We think you need these skills to ace Data Scientist / ML Engineer in London
Some tips for your application 🫡
Tailor Your CV:Make sure your CV highlights relevant experience in data science and machine learning. Focus on projects where you've built predictive models or worked with marketing use cases, as this aligns closely with the job description.
Craft a Compelling Cover Letter:In your cover letter, express your passion for data science and how your skills can contribute to the agency's goals. Mention specific tools and techniques you are proficient in, such as Python, SQL, and advanced ML methods, to demonstrate your fit for the role.
Showcase Your Projects:If possible, include links to your portfolio or GitHub where you have showcased relevant projects. Highlight any work involving causal AI, NLP, or other advanced techniques mentioned in the job description to stand out.
Prepare for Interviews:Anticipate questions related to your technical skills and past experiences. Be ready to explain complex analyses in simple terms, as you'll need to communicate effectively with both technical and non-technical stakeholders.
How to prepare for a job interview at Xcede
✨Showcase Your Technical Skills
Be prepared to discuss your experience with Python, SQL, and machine learning models. Bring examples of projects you've worked on, especially those involving predictive analytics or marketing use cases, to demonstrate your expertise.
✨Communicate Clearly
Since you'll be presenting technical concepts to both technical and non-technical stakeholders, practice explaining complex ideas in simple terms. This will show your ability to bridge the gap between data science and business needs.
✨Demonstrate Leadership Potential
If you have experience leading teams or projects, be ready to share specific examples. Highlight how you've guided others, upskilled team members, or managed multiple projects simultaneously, as this role involves leading a team of data scientists.
✨Prepare for Scenario-Based Questions
Expect questions that assess your problem-solving skills and ability to deliver real business impact. Think of scenarios where you've used data to drive campaign performance or improve marketing strategies, and be ready to discuss the outcomes.
